Artificial Neural Networks designed to simulate of the human brain require an ability to learn a variety of tasks that is not required by those designed to accomplish a specific task. Supervised learning is a mechanism by which an artificial neural network can learn by receiving a number of inputs with a correct output already known.
Artificial Neural Networks intended to mimic the human brain need to be proficient in acquiring diverse skills, unlike those specifically designed for a particular function. Supervised learning allows an artificial neural network to acquire knowledge by receiving a range of inputs accompanied by recognized correct outputs.