The hypothesis space of linear regression is

 The hypothesis space of linear regression is:

d. The space of all possible linear functions

Why?

• In machine learning, the hypothesis space is the set of all functions a model can choose from.

• For linear regression, this means all functions of the form:

$$h(x)={\beta }_0+{\beta }_1{x}_1+{\beta }_2{x}_2+\cdots +{\beta }_p{x}_p$$

where the $\beta$ values are parameters.

• So the model can only explore linear combinations of features — not arbitrary nonlinear functions.