Tree Boosting With XGBoost - Why Does XGBoost Win "Every" Machine Learning Competition?

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Machine learning algorithms to predict flow condensation heat transfer coefficient in mini/micro-channel utilizing universal data (2020, methodology): “Including highly correlated varibles doesn‘t provide any benefit to model performance and are ften handled naturally by getting dropped in several tree based lgorithms [96] .”
Enhancing the prediction of student performance based on the machine learning XGBoost algorithm (2021, methodology): “The impact of the XGBoost algorithm has been widely recognized in many machine learning and data mining challenges, where it has become a more commonly used and popular tool among Kaggle’s competitors and the data scientist of the industry (Nielsen, 2016).”