Adaboost (Adaptive Boosting) is a powerful Machine Learning algorithm that builds a strong classifier by sequentially combining many "weak" ones. It iteratively adjusts the weights of misclassified data points, compelling subsequent weak learners to focus on these difficult examples, thereby refining the overall prediction through Ensemble Learning.