<prompt> Hlalosa boemo moo algorithm e fanoeng e ka sebelisoang ho rarolla bothata.K-Haufi le Baahelani KNN Algorithm  <response>: Instruction in English: Describe a scenario where the given algorithm can be used to solve a problem. . Response in English: A common scenario where KNN can be used is in the classification of data on a recommendation platform. Lets consider a music streaming service that aims to create personalized playlists for each of its registered users. Based on data gathered from their listening habits and musical preferences, the platform plans to use the KNN algorithm to suggest new songs that each user might enjoy.Each user is represented by a set of data points features such as their age, gender, favorite genre, artist, and the average number of minutes spent on the platform per day. When a user logs into their account, the system needs to generate a list of recommended songs that suit their taste. The KNN algorithm starts by calculating the distance between the data points of the user in question and all the other users in its database. It then selects the k number of users closest to the target user i.e., the users having the smallest distance. These are the k-nearest neighbors.From here, the system examines the listening history of these k-nearest neighbors and creates a collection of songs that were most frequently played by this group. A list is then generated and recommended to the target user. This way, the KNN algorithm can be used in generating an accurate and personalized playlist for each user of the music streaming service. . Response in Sesotho: Boemo bo tloaelehileng moo KNN e ka sebelisoang ke ho hlophisoa ha data sethaleng sa likhothaletso. Ha re nahaneng ka tšebeletso ea ho phallela mino e ikemiselitseng ho iketsetsa manane a bapaloang bakeng sa e mong le e mong oa basebelisi ba eona ba ngolisitsoeng. Ho ipapisitsoe le lintlha tse bokelletsoeng mekhoeng ea bona ea ho mamela le likhethong tsa mino, sethala se rera ho sebelisa algorithm ea KNN ho fana ka maikutlo a lipina tse ncha tseo mosebelisi e mong le e mong a ka li thabelang. Mosebelisi e mong le e mong o emeloa ke sehlopha sa lintlha likarolo tse kang lilemo tsa bona, bong, mofuta oo a o ratang, sebini le kakaretso ea metsotso e sebelisoang sethaleng ka letsatsi. Ha mosebelisi a kena akhaonteng ea bona, sistimi e hloka ho hlahisa lenane la lipina tse khothalelitsoeng tse lumellanang le tatso ea tsona. KNN algorithm e qala ka ho bala sebaka se pakeng tsa lintlha tsa data tsa mosebelisi eo ho buuoang ka eena le basebelisi ba bang kaofela polokelong ea eona. E ntano khetha palo ea k ea basebelisi ba haufi haholo le mosebelisi ea shebiloeng ke hore, basebelisi ba nang le sebaka se senyenyane haholo. Bana ke baahelani ba haufi le k. Ho tloha mona, tsamaiso e hlahloba histori ea ho mamela ea baahisani bana ba k-haufi le ho etsa pokello ea lipina tse neng li letsoa hangata ke sehlopha sena. Joale lethathamo le hlahisoa me le khothaletsoa ho mosebelisi ea lebelloang. Ka tsela ena, algorithm ea KNN e ka sebelisoa ho hlahisa lenane la lipina le nepahetseng le la motho ka mong bakeng sa mosebelisi e mong le e mong oa tsebeletso ea ho tsamaisa mmino. 