Cross-domain learning involves transferring knowledge and skills from one domain to enhance learning in another, often leveraging similarities between domains to improve performance and efficiency. It is crucial in scenarios where data is scarce or expensive to obtain in the target domain, and it underpins many applications in machine learning and artificial intelligence, such as transfer learning and domain adaptation.