The $k$-center problem is where we a given a graph $G(V,E)$, an integer $k$, a distance metric $d$ and we want to find a subset $C\subseteq V$ (such that $|C|\leq k$) which minimizes the following function: $\max_{v\in V}\min_{c\in C}d(v,c)$.
I am trying to understand the proof that the $Gon$ algorithm is a 2-approximation. The algorithm arbitrarily selects the initial center and loops for $k-1$ iterations, where at each iteration it adds the vertex which is furthest away from its nearest center as a new center.
The full proof that this algorithm gives a 2-approximation is described in Gonzalez, Clustering to minimize the maximum intercluster distance. The cost of the optimal solution is $OPT(V)$ and they describe the term "$(k+1)$-clique of weight $h$ for $V$":
Set $T$ is said to form a $(k+1)$-clique of weight $h$ if the cardinality of set $T$ is $k + 1$ and every pair of distinct elements in $T$ are at least $h$ units apart.
The part that I don't understand is the following lemma:
Lemma 2.1: If there is a $(k+1)$-clique of weight $h$ for $S$, then $OPT(V)\geq h$.
My question is, what is the proof for this lemma?