Meta-learning is an area of artificial intelligence that seeks to develop algorithms that can learn to learn, i.e., adapt to new tasks or environments more efficiently. This is achieved by using higher-level machine learning techniques to capture patterns and relationships in training data and apply this experience to learn new tasks with a smaller number of examples. The goal is to create artificial intelligence systems that are more adaptive, flexible and able to generalize from limited data.