Ensemble learning combines predictions from multiple models to improve machine learning performance. This overview covers bagging, boosting, and stacking methods, including popular algorithms like random forest, AdaBoost, and XGBoost. The study explains these algorithms' mathematical and algorithmic details, which can benefit machine learning researchers and practitioners.