Underfitting
Also: underfit, under-fitting
The model lacks the capacity, features or training time to represent the relationship, giving high error on both training and test data. It is the high-bias side of the bias-variance tradeoff.
Example
Fitting a straight line to points that follow y = x² leaves large errors everywhere; likewise k-NN with k equal to the whole dataset just predicts the majority class.