XGBoost is an optimized distributed gradient boosting library designed to be highly efficient, flexible, and portable. It stands for eXtreme Gradient Boosting and is used for supervised learning tasks, such as classification and regression. XGBoost implements machine learning algorithms under the Gradient Boosting framework and provides parallel tree boosting that speeds up model training. Its features include regularization to prevent overfitting, support for missing values, and handling sparse data. XGBoost is widely known for its performance and accuracy and has been used to win numerous machine learning competitions.