Data labeling is the process of adding metadata to raw data to make it usable for machine learning and AI algorithms. This metadata, or labels, can include categories, keywords, or other types of annotations that help the algorithms understand and process the data more efficiently. Data labeling is a critical step in the development of AI applications, as it ensures that the algorithms are trained on high-quality data that accurately reflects the real-world scenarios they will be deployed in.