Add an `AbstractShiftedProximableNLPModel`

In `RegularizedOptimization.jl`, we often construct subproblems of the form
```math
\min_s \varphi(s; x) + \psi(s; x) + \frac{\sigma}{2} \lVert s \rVert^2
```
where $$\varphi(s; x) = f(x) + \nabla f(x)^T s + \frac{1}{2} s^T B(x) s$$ and $$\psi$$ is a shifted model of a regularized $$h$$.

Just like `RegularizedNLPModel` wraps both an `NLPModel` and a regularizer `h`, I suggest we add an `AbstractShiftedProximableNLPModel <: AbstractRegularizedNLPModel` that wraps a shift of a `RegularizedNLPModel`.

Related: https://github.com/JuliaSmoothOptimizers/RegularizedOptimization.jl/pull/316.