The proof is as follows:
Consider $C^{-1}-(C+\Lambda)^{-1} $
$$
C^{-1}-(C+\Lambda)^{-1} = C^{-1} \left( [C+\Lambda] - C\right) (C+\Lambda)^{-1}
=C^{-1} \Lambda (C+\Lambda)^{-1} = C^{-1} \Lambda (I+C^{-1}\Lambda)^{-1} C^{-1}=
C^{-1} (\Lambda^{-1}+C^{-1})^{-1} C^{-1}
$$
The last matrix is clearly positive definite. Hence, its diagonals must be positive.
This shows that
$$\left[C^{-1}\right]_{ii} >\left[(C+\Lambda)^{-1}\right]_{ii}$$
Added in response to OP's question
If $\Lambda$ is only positive semi definite, then $\Lambda + \epsilon I$ is positive definite for any $\epsilon >0$. Hence, by virtue of previous argument
$$\left[C^{-1}\right]_{ii} >\left[(C+\Lambda+\epsilon I)^{-1}\right]_{ii}, \forall \epsilon > 0$$
By continuity argument, as $\epsilon \to 0$
$$\left[C^{-1}\right]_{ii} \ge \left[(C+\Lambda)^{-1}\right]_{ii}$$
Note that $\Lambda + \epsilon I$ is positive definite for any $\epsilon >0$ because
$$
x^T (\Lambda + \epsilon I) x = x^T \Lambda x + \epsilon x^T x \ge \epsilon x^T x \gt 0 \text{ if $x \neq 0$}$$
The trick of adding $\epsilon I$ to a semi-definite matrix to make is positive definite and then taking the limit as $\epsilon \to 0^+$ is the standard way to extend results from definite to semidefinite.