Not necessarily.
Why $\mu$ is not necessarily the uniform product measure:
Even if the orbit of $x$ is dense, there could be arbitrary bias in the frequency it visits different regions. For instance, let $w^{(1)}, w^{(2)}, \ldots$ be an enumeration of $\{0,1\}^*$ (i.e., all finite binary words). Construct $x$ as
$$x = \cdots 0\,0\,0\,\underline{0}\,0^{n_1}\,w^{(1)}\,0^{n_2}\,w^{(2)}\,0^{n_3}\,w^{(3)}\cdots\;.$$
(Underline denotes the symbol at the origin.) The orbit of $x$ is clearly dense, but if you choose $n_1, n_2,\ldots$ appropriately, the measures $\mu_n$ converge to the Dirac measure concentrated at the all-$0$ sequence. (More specifically, the frequency of indices $i$ such that the block $x_{[i,i+k)}$ is anything but $0^k$ converges to $0$.)
Why $\mu$ is not necessarily ergodic:
Repeat a similar construction this time with
$$x = \cdots 0\,0\,0\,\underline{0}\,0^{n_1}\,w^{(1)}\,1^{n_2}\,w^{(2)}\,0^{n_3}\,w^{(3)}\,1^{(n_4)}\cdots\;.$$
(That is, the blocks separating $w^{(i)}$s are alternately all-$0$s and all-$1$s.)
Again, choosing $n_1,n_2,\ldots$ suitably, the measures $\mu_n$ converge to the uniform convex combination of the two Dirac measures concentrated at the all-$0$ and all-$1$ sequences.
In fact, there is a theorem of Kakutani stating that every probability measure on $\{0,1\}^{\mathbb{Z}}$ can be obtained as the orbit statistics of some sequence in $\{0,1\}^{\mathbb{Z}}$. Modifying such a sequence slightly, you can make sure that it has dense orbit.