Bias-Variance Tradeoff

The fundamental balance in machine learning between a model that's too simple (high bias) and one that's too complex (high variance). It's like Goldilocks finding the perfect porridge - too simple and you miss important patterns, too complex and you memorize noise instead of learning real relationships. The sweet spot minimizes both bias and variance for the best overall performance.