What is the difference between supervised and unsupervised learning?

Supervised learning involves training a model on labeled data (input-output pairs), with the goal of predicting the output for new, unseen inputs. Examples include regression and classification.
Unsupervised learning involves training a model on unlabeled data to find hidden patterns or structures. Examples include clustering and dimensionality reduction.