What is the difference between supervised and unsupervised learning?

Supervised learning trains on labelled data — each example has a known target — to predict labels for new inputs (e.g. spam vs not-spam, house prices). Unsupervised learning works on unlabelled data to find structure, such as clustering customers into segments or reducing dimensionality. A third category, reinforcement learning, learns from reward signals through trial and error. The quick tell: supervised needs labels and predicts; unsupervised has no labels and discovers patterns.