Bias Variance Irreducible Error and Model Complexity Trade off

Supervised Machine Learning can be summarized as shown below

Training data is fed to algorithm, which results in target function derivation. Test data is fed into this target function to get the prediction.

As an example, for simple linear regression algorithm follows equation h(y)=b0+b1X1.