If ${\bf x}={\bf a}+{\bf b}i$, ${\bf y}={\bf c}+{\bf d}i$ in
$C^n$, define vectors
${\bf u}=({\bf a},{\bf b})$, ${\bf v}=({\bf c},{\bf d})$,
${\bf w}=(-{\bf d},{\bf c})$ in $R^{2n}$.
Then
$$
{\bf x}\cdot {\bf y} = {\bf u}\cdot {\bf v}+i{\bf u}\cdot {\bf w}
$$
so the real and imaginary parts of ${\bf x}\cdot {\bf y}$ have exactly
the geometric interpretations you are familiar with,
as applied to ${\bf u}$, ${\bf v}$ and ${\bf w}$, where ${\bf w}$
is a rotation of ${\bf v}$.
But I think it is best to separate some of the concepts a bit.
If we take "geometry" to refer to concepts of distance and
angle, then projection goes beyond geometry because it involves
linear combinations; we don't really project a vector to a vector,
instead we project it to a subspace. And, while it is true that
the projection of ${\bf x}$ to the span of ${\bf y}$ in $C^n$ gives the
point of the subspace closest to ${\bf x}$, the word to focus on is
not so much "closest" (geometry), but "subspace" (algebra).
The simplest example of this is probably in $C^1$ versus $R^2$:
The projection of $x=a+bi$ onto the span of $1$ is $x$ itself.
But the projection of $(a,b)$ onto the span of $(1,0)$ is $(a,0)$.
In both cases you have the closest point; what has changed is
the subspace rather than the concept of distance.