In-context learning is the ability of a large language model to learn a task from examples placed directly in the prompt, without any retraining. You show the model a few input-output pairs, and it infers the pattern and applies it to new cases. For instance, an HR team can paste three examples of CVs labeled «junior» or «senior» and ask the model to classify the next hundred the same way. It turns a general-purpose model into a specialized tool in seconds.