XGBoost (Extreme Gradient Boosting) is a highly efficient machine learning algorithm based on ensemble learning, specifically gradient-boosted decision trees. It builds trees sequentially, with each new tree correcting errors from the previous ones. XGBoost consistently wins Kaggle competitions and is a go-to algorithm for tabular data tasks like fraud detection, customer churn prediction, and credit scoring. It is fast, handles missing values natively, and includes built-in regularization to prevent overfitting.