"Data annotation" involves the process of labeling or tagging datasets to provide context, making them usable for machine learning applications. This preparation step is crucial for training models, as it helps the algorithms understand the relationships within the data. Annotated data can include various formats, such as images, text, and video, categorizing elements like objects, sentiments, or actions. High-quality data annotation ensures that machine learning models are effective and accurate, driving better predictions and performance in real-world applications.