Supervised learning is a type of machine learning where an algorithm learns from a labeled dataset, which consists of input-output pairs. The algorithm's goal is to learn a function that maps inputs to outputs, so that it can predict the output for new, unseen inputs. It is commonly used for classification and regression tasks.
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