Apprenticeship learning is a machine learning approach where an agent learns to perform tasks by observing and mimicking an expert, rather than being explicitly programmed or trained with a reward signal. This technique is particularly useful in environments where defining a reward function is difficult or where expert demonstrations are more readily available than labeled data.