If your matrices are complex, then $B^*$ has no derivative wrt $B$; it's the same for your function $f$ (cf. runway44's comment). But it works if your matrices are real.
Lett $f:B\in M_{m,k}(\mathbb{R})\mapsto tr((A-BC)^T(A-BC))$ (the Frobenius norm).
Then $Df_B:H\in M_{m,k}\mapsto -2tr((A-BC)^THC)$ and
$D^2f_B:(H,K)\in (M_{m,k})^2\mapsto 2tr(C^TK^THC).$
We see that $f$ is convex because $D^2f_B(H,H)=2tr(C^TH^THC)\geq 0$.
Since the second derivative does not depend on $B$, the second order Taylor's formula is an equality
$(*)$ $f(B+H)=f(B)-2tr((A-BC)^THC)+tr(C^TH^THC)$.
Of course, $f(B+H)\geq f(B)-2tr((A-BC)^THC)$.
EDIT. Answer to the OP. In the complex case, the equality $(*)$ becomes
$f(B+H)=f(B)-2Re(tr((A-BC)^*HC))+tr(C^*H^*HC)$ (it's a formal equality and not a Taylor's formula).
We deduce that $f(B+H)\geq f(B)-2Re(tr((A-BC)^*HC))$.