Model validation is the process of evaluating a model's performance and reliability by comparing its predictions against real-world data or a holdout dataset. It ensures that the model generalizes well to unseen data, preventing overfitting and underfitting, and is crucial for maintaining the model's credibility and effectiveness in practical applications.