What is the difference between supervised, unsupervised, and reinforcement learning?

Supervised learning trains on labelled input-output pairs. Unsupervised learning finds structure in unlabelled data (e.g. clustering). Reinforcement learning trains an agent to maximise reward through trial and error in an environment. Most LLMs are pre-trained with self-supervised learning, then fine-tuned with reinforcement learning from human feedback (RLHF).