LightGBM is a gradient boosting framework written in C++ that implements decision tree algorithms for classification, ranking, and other machine learning tasks. It supports distributed training, GPU acceleration via CUDA, and provides wrappers for Python and R. It is widely used in Kaggle competitions and production ML pipelines as a core ML algorithm library.