Here's my attempt:
Let $ = (x_1, x_2, x_3)$ and $ = (y_1, y_2, y_3)$
The cross product of $, $ is $⨯=(x_2y_3-x_3y_2, x_3y_1 - x_1y_3, x_1y_2 - x_2y_1)$
And linear independence of $, $ means that if $a + b = 0$, then $a = b = 0$, i.e. $a(x_1, x_2, x_3) + b(x_1, x_2, x_3) = 0 ⇒ a = b = 0$
So if cross product is nonzero, then $ x_2y_3-x_3y_2 + x_3y_1 - x_1y_3 + x_1y_2 - x_2y_1 ≠ 0, i.e. x_1(y_2-y_3)+x_2(y_3-y_1) + x_3(y_1 - y_2) ≠ 0$
And then I'm just getting confused.
I can't seem to connect the two in a formal proof.
Your problem is equivalent to the following:
To prove this assume first that $x$ and $y$ are linearly dependent, i.e. there is some $a\in\mathbb R$ such that $x=ay$. Then it is easy to see that $x\times y=(0,0,0)$ (just plug in).
For the converse assume now that $x\times y=(0,0,0)$. Then $x_2y_3=x_3y_2$, $x_3y_1=x_1y_3$ and $x_1y_2=x_2y_1$. If $y\neq0$, then one entry is $\neq0$, say $y_3\neq0$. Then $x_2=\frac{x_3y_2}{y_3}$, $x_1=\frac{x_3y_1}{y_3}$. Thus, $(x_1,x_2,x_3)=\frac{x_3}{y_3}\cdot(y_1,y_2,y_3)$, so $x$ and $y$ are linearly dependent.
Here is an alternative proof (for the converse) using the identity $v\cdot(x\times y)=\det(v,x,y)$ for each $v\in\mathbb R^3$, i.e. assume $x\times y=(0,0,0)$. Take a vector $v\notin\text{span}\{x,y\}$. If $x$ and $y$ were linearly independent, then $\{v,x,y\}$ were a basis of $\mathbb R^3$ and therefore $\det(v,x,y)\neq0$, contradicting $\det(v,x,y)=v\cdot(x\times y)=0$.