Learning process with the help of a teacher is called supervised learning. In supervised learning the algorithm generates a function that maps inputs to desired outputs. One standard formulation of the supervised learning task is the classification problem: the learner is required to learn a function which maps a vector into one of several classes by looking at several input-output example of the function.
Learning process without teacher is called unsupervised learning. During training the machine learning algorithm receives the input pattern and organizes these patterns to form clusters. When a new input pattern is applied, gives an output response indicating the cluster to which the input pattern belongs.
Similar to supervised learning. In this learning process only critic information is available not the exact information. The learning process is done based on the critic information and a feedback signal called reinforcement signal is sent back from output to the input.’