Supervised learning is a type of machine learning where the model is trained on a labeled dataset. This dataset consists of input-output pairs, and the goal is for the model to learn the mapping from inputs to outputs so it can predict the output for new, unseen inputs. The learning process involves adjusting the model's parameters to minimize the error between its predictions and the actual outputs.
