Bias Variance
Bias-variance is a fundamental dilemma in Machine Learning, revealing how a model's predictions vary from the true function. High bias means a model is too simple (underfitting), missing patterns, while high variance means it's too complex (overfitting), sensitive to noise and struggling with Generalization on unseen data.