Classification and regression are two types of supervised learning.
Classification is a type of supervised learning in which the output is a discrete label, such as a yes/no or a category. For example, a classification algorithm might be used to identify whether an email is spam or not.
Regression is a type of supervised learning in which the output is a continuous value. For example, a regression algorithm might be used to predict the price of a house based on its size and location.