Synthetic data generation refers to the creation of new datasets that simulate real-world data but are artificially generated. It involves creating data points that share similar statistical characteristics and patterns as the original data, without revealing any sensitive or confidential information. This technique is commonly used in various fields, such as ML, data analysis, and privacy-preserving research.