Zero-shot learning is a machine learning approach that enables a model to recognize and categorize data it has never seen before by leveraging semantic relationships and auxiliary information. It is particularly useful in scenarios where labeled data is scarce or where new categories emerge frequently, allowing for more flexible and adaptive AI systems.