I think there is a much easier proof if you know some linear algebra.
As in the text, it's enough if we show that
$$||\beta_1 x_1 + \beta_2 x_2 + \ldots + \beta_n x_n|| \geq c $$ where $\sum_{j=1}^{j=n} |\beta_j| = 1 $ or $|\beta|_1 = 1$.
Let $X$ be the matrix whose nth column is $x_n$. Let $\beta$ be the vector whose nth entry is $\beta_n$ Then we want to show $||X \beta || \geq c$, where $||\beta||_1 = 1$.
Consider the singular value decomposition of $X$. There exist positive real scalars $s_1, \ldots, s_n$ and orthonormal bases $e_1, \ldots, e_n$ and $f_1, \ldots, f_n$ such that
$$X \beta = s_1 \langle \beta, e_1\rangle f_1 + \ldots+ s_n \langle \beta, e_n\rangle f_n $$
Let $s_k = \min\{s_1, \ldots, s_n \}$. Since $f_1, \ldots, f_n$ are orthonormal, we
\begin{align}
||X \beta||_2^2 &= s_1^2 \langle \beta, e_1\rangle^2 + \ldots+s_n^2 \langle \beta, e_n\rangle^2 \\
&\geq s_k^2 \left( \langle \beta, e_1\rangle^2 + \ldots +\langle \beta, e_n\rangle^2 \right)
\end{align}
Since $e_1, \ldots, e_n$ are orthonormal, $\left( \langle \beta, e_1\rangle^2 + \ldots +\langle \beta, e_n\rangle^2 \right) = || \beta ||_2^2$. If $||\beta||_1 = 1$, then $||\beta||_2 \leq 1$. This implies:
$$
\begin{align}
||X \beta||_2 &\geq s_k
\end{align}
$$
(I've realized that I've implicitly assumed that each $x_j$ are n-dimensional. For other dimensions, the argument should only change trivially.)