Synthetic Data is artificially generated data that replicates the statistical properties and structure of real-world data without being directly collected from physical sources. It is created using methods such as simulations, generative models, or rule-based systems to support tasks like training, testing, and validating machine learning models. Synthetic data helps address data scarcity, privacy concerns, and labeling costs while enabling controlled experimentation across applications in computer vision, healthcare, finance, and autonomous systems.