<prompt> Theha algorithm e ka hlahisang mantsoe a haufi-ufi a nyallanang a fuoang sehlopha sa mantsoe a kenyelelitsoeng.nan  <response>: Instruction in English: Create an algorithm that can output the closest matching words given a set of input words. . Response in English: Here is an algorithm that can find the closest matching words given a set of input words:1. Initialize: Initialize a list called input_words to store the input words, and a variable min_distance to track the minimum edit distance between any two words in the list. Set min_distance to a large value initially.2. Input: Take the input words from the user, split them with the delimiter space, comma, etc and store them in the input_words list. 3. Compute the edit distances: For every pair of words in input_words, compute the edit distance, which is the minimum number of operations required to transform one word into the other. The operations can be insertions, deletions, or substitutions of a single character. This can be done using dynamic programming, where a 2D table is constructed to find the minimum number of operations. 4. Find the closest matching words: While computing the edit distances, keep track of the minimum distance and the pair of words that resulted in that minimum distance. This can be done by updating the min_distance variable and storing the pair of words that resulted in the minimum distance. 5. Output: Once all pairs of words have been checked, output the pair of words that resulted in the minimum edit distance. These are the closest matching words in the given set of input words. This algorithm can be implemented in various programming languages using nested loops, dynamic programming, and 2D arrays. . Response in Sesotho: Mona ke algorithm e ka fumanang mantsoe a haufi-ufi a nyallanang a fuoang sehlopha sa mantsoe a kenyelelitsoeng: 1. Qalisa: Qala lenane le bitsoang input_words ho boloka mantsoe a kentsoeng, le phetoho min_distance ho sala morao liphetoho tse fokolang. sebaka pakeng tsa mantsoe afe kapa afe a mabedi lenaneng. Beha min_distance ho boleng bo boholo qalong. 2. Kenyo: Nka mantswe a kentsweng ho tswa ho mosebedisi, o a arole ka delimiter sebaka, phegelwana, jj mme o a boloke lenaneng la input_words. 3. Bala bohole ba ho hlophisa: Bakeng sa para e ngoe le e ngoe ea mantsoe ho input_words, bala sebaka sa ho fetola, e leng palo e fokolang ea tsebetso e hlokahalang ho fetolela lentsoe le leng ho le leng. Tsebetso e ka ba ho kenya, ho hlakolwa, kapa ho kenya mongolo o le mong. Sena se ka etsoa ka ho sebelisa mananeo a matla, moo tafole ea 2D e hahiloeng ho fumana palo e fokolang ea tsebetso. 4. Batla mantsoe a haufi a nyalelanang: Ha u ntse u khomphutha bohole bo fetotsoeng, boloka tlaleho ea bohole bo fokolang le para ea mantsoe a bakileng sebaka seo bonyane. Sena se ka etsoa ka ho nchafatsa phapang ea min_distance le ho boloka para ea mantsoe e entseng hore ho be le sebaka se fokolang. 5. Sephetho: Hang ha lipara tsohle tsa mantsoe li se li hlahlojoe, hlahisa para ea mantsoe a entseng hore ho be le sebaka se fokolang sa ho fetola. Ana ke mantsoe a tšoanang a haufi-ufi sehlopheng se fanoeng sa mantsoe a kenyelletsoang. Algorithm ena e ka kengoa tsebetsong ka lipuo tse fapaneng tsa lenaneo ho sebelisa li-loops tse behiloeng, mananeo a matla, le li-arrays tsa 2D. 